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Course Schedule

Date Topic Suggested Readings Reference Homework
Aug.
26, 30
Introduction [En] [Fr]
Mathematics [En] [Fr]
Machine Learning Basics [En] [Fr]
Deep Learning Book
Chap. 2
Chap. 3
Chap. 5
Sep.
9, 6
Feedforward Neural Networks & Optimization Tricks [En] [Fr]
Deep Learning Book
Chap. 6
Chap. 7
Chap. 8
Sep.
16, 13
Introduction to Pytorch
PyTorch Part 1
PyTorch Part 2
Python Numpy Tutorial
Pytorch's official tutorial
Neural Network from Scratch
Dive into Deep Learning
HW1 [En] [Fr]
Sep.
23, 20
Convolutional Neural Networks & Recurrent Neural Networks [En] [Fr]
Deep Learning Book
Chap. 9
Chap. 10
ResNet
GRU
DenseNet
Oct.
1, Sep 27
NLP Basis [En] [Fr]
Word2Vec
GloVe
SGNS
Oct.
7, 4
Attention, Transformers [Fr] [En]
The annotated Transformer (blog)
Transformer
Rotary Position Embedding
Relative Position Embedding
ViT
Reformer
FlashAttention
Oct.
16, 11
Course Project QA
HW2 [En] [Fr]
Oct.
28, 25
Large Language Models I [Part-1 Fr] [Part-2 Fr] [Part-1 En] [Part-2 En]
BERT
GPT-3
LoRA
Scaling Law
GPT in 60 Lines of NumPy
XLNet
UL2
Nov.
04, 01
Large Language Models II [En] [Fr]
Chain-of-Thought
Prompt Engineering (Blog by Lilian Weng)
InstructGPT
Automatic Prompt Engineer
Nov.
11, 08
Generative Models [En] [Fr]
VAE
Evidence Lower Bound ELBO — What & Why (Blog)
GAN
Diffusion Probabilistic Model
beta-VAE
CycleGAN
Latent Diffusion
Nov.
18, 15
Multi-Modality Learning [En] [Fr]
DALL·E3
Sora
Kling
Flamingo
LLaVA
InstructBLIP
Nov.
25, 22
Graph Representation Learning [En] [Fr]
GCN
Graph Neural Networks Implementation Tutorial
DeepWalk
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